Adult-onset type 1 diabetes (T1D) is often misclassified as type 2 diabetes (T2D), resulting in delayed treatment, missed opportunities for referrals to specialists and increased risk of complications including diabetic ketoacidosis. An electronic medical record (EMR)-based algorithm—originally trained on a large national EMR dataset to identify likely misclassified adult-onset T1D cases—was tested and retrained on a health information exchange (HIE) dataset from HealthShare Exchange (HSX). Promising results were achieved on historical data, particularly when using the retrained algorithm. However, its prospective validation is essential to more reliably assess its clinical utility and real-world precision in flagging high-risk patients for clinician review.

This is a prospective, multicentre, non-interventional cohort study in two HSX-member healthcare organisations (HCOs) in southeastern Pennsylvania. At the onset of the study, all adult T2D patients are scored by the algorithm analysing HIE data on relevant predictors found in the 24-month lookback period. Patients meeting a prespecified score threshold estimated in retrospective testing to yield 10% recall will be presented to designated endocrinology or primary care providers for structured chart review, attribution confirmation and guideline-concordant follow-up (including autoantibody testing where appropriate). The primary endpoint is positive predictive value for confirmed adult-onset T1D among flagged patients. Secondary endpoints characterise operational cascade metrics (attribution, provider recommendation, test ordering/results and diagnosis updates) along with 95% CIs. Exploratory endpoints will assess provider adoption, interpretability and workflow integration via structured provider interviews.

This study was reviewed and approved by Advarra Institutional Review Board (protocol Pro00075945). The Institutional Review Board waived patient informed consent and granted a full waiver of HIPAA authorisation for patient records, while providers were required to provide written informed consent. HSX data were accessed and shared under its member-defined use cases. Findings will be disseminated via peer-reviewed publications and conference presentations. Reporting will follow Strengthening the Reporting of Observational Studies in Epidemiology guidance for cohort studies.

Spirituality has gained increasing attention in healthcare, particularly in palliative care, as it supports meaning, purpose and connection during illness. While literature extensively explores patients’ spiritual needs, growing evidence highlights the importance of addressing the spiritual needs of caregivers and healthcare professionals. Caregivers and relatives often face emotional, ethical and practical challenges during prolonged care pathways, impacting their well-being. Limited training and tools can hinder spiritual care, contributing to distress and burnout among professionals and unmet needs for families. Addressing spirituality in neurodegenerative disease palliative care is essential for holistic, person-centred approaches that foster coping, hope and ethical decision-making. This scoping review aims to map evidence on spiritual needs and challenges of caregivers, relatives and healthcare staff in end-stage neurodegenerative disease care.

This review will follow the Joanna Briggs Institute framework (JBI) for scoping reviews. The search and reporting process will be guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews checklist. Inclusion criteria followed JBI’s population, concept and context framework with no date or geographical limits; only English and Italian sources ensured accurate interpretation. Searches will use university-access databases and grey literature to capture policy and non-peer-reviewed sources. Databases selected: PubMed, CINAHL, APA PsycINFO and Scopus for comprehensive, multidisciplinary coverage. This inclusive approach is aligned with the purpose of scoping reviews, which aim to map the breadth and depth of available literature. Researchers independently screened titles/abstracts in Rayyan software with blinding, resolved discrepancies collaboratively, piloted and refined extraction tables, and jointly synthesised themes through iterative meetings to ensure rigour and consensus. Findings will highlight existing knowledge, identify gaps and inform future research and practice.

Since secondary data will be analysed, no ethical approval is required. The results will be disseminated through publications subject to peer review. The protocol has been registered with the Open Science Framework https://doi.org/10.17605/OSF.IO/X9275